This is my final presentation on Obamacare. I discuss what Obamacare is, as well as the issues associated with it. I show two data visualizations that I created in lab using data from Twitter (tweets using the hashtag #Obamacare). I created a map of geolocations as well as a word cloud, which displays the most commonly used words in tweets. I also related my findings to software-sorted geographies and the filter bubble. Hope you guys enjoy!

1. #Obamacare
Danny Dinno

2. What is Obamacare?
-Affordable Care Act
-Signed into law by Obama on 3/23/10
-Better access to affordable healthcare
-Lowers cost of healthcare
-Can stay on parents’ plan until 26

3. Problems with Obamacare
-More taxes/tax rates increasing
-Higher premiums
-Increase in prescription drug costs
-Some families lost their private insurance
-Increasing national debt
-President Trump → Repeal and Replace

4. Global Issue? Just United States?
-Map of Geolocations
-Tweets only had geolocations in
United States (only 0.01% mapped)
-Issue primarily pertains to Americans
-Based on the small amount of mapped
tweets, Obamacare does not
affect people outside the United States

5. Common Words Used in Tweets
Used 45 words in the word cloud
- “Repeal”
- “potus”
- “speakerryan”
- “aca”
- “gop”
- “repealandreplace”
All words in English → Issue only in America?
*“speakerryan” and “potus” are two biggest nodes in
SNA*

6. “Software-Sorted Geographies” (Graham)
and the Filter Bubble
- Data shows the different types of people
tweeting about Obamacare and where they live
- These people are grouped together by a filter
bubble → Biased based on area because people
are only seeing one side of the issue, causing
them to conform to this opinion
- Obamacare supporters tend to live in the same
area while Trump/repealing Obamacare
supporters tend to live in the same area
-Political issue → democrats vs. republicans

7. Summary
-Huge controversy as to whether or not repeal Obamacare
-Geolocations on map were only in United States indicating that this is primarily
an issue that affects people in this country (only 0.01% of tweets mapped)
-Word cloud only has words in English → issue in United States??
- Software-sorted geographies and filter bubble → grouping people based on
their opinion on Obamacare and where they live

8. Works Cited
Neff G. 2013. WHY BIG DATA WON’T CURE US. Big Data 1:117-123.
Yau, N. (2013). Data points: visualization that means something. Indianapolis: John Wiley & Sons.
Pear, Robert and Kaplan, Thomas. 2017. "House G.O.P Leaders Outline Plan to Replace Obama Health
Care Act". New York Times.
Graham, Stephen D.H. “Software-Sorted Geographies.” Progress in Human Geography 29.5 (2016):
562-80. Web.
<http://www.dourish.com/classes/readings/Graham-SoftwareSortedGeographies-PHG.pdf>.